In this comprehensive literature-based study, the LIINES presents a logical case for integrating power grid assessment methods into a holistic enterprise control framework. Such a framework is explicitly techno-economic and merges methods power systems engineering and economics. To support the argument, the LIINES has conducted the most comprehensive review of renewable energy integration studies completed to date.

The paper discusses the need for change in the assessment of the electricity grid as a result of five driving forces. The driving forces are identified as: decarbonization, growth of electricity demand, transportation electrification, electric power deregulation, and increasing numbers of responsive (“smart”) consumers. These five drivers require the steadily increasing penetration of solar and wind generation as well as evolving capabilities to support demand side management for the tremendous diversity of loads that connect to the electrical grid. The integration of these three new grid technologies of renewable energy, electric vehicles, and demand side resources ultimately imposes fundamental changes to the grid’s structure and behavior.

The paper argues that the future electric grid’s needs for reliability, cost efficiency and sustainability necessitates a holistic assessment approach. Figure 1 shows a guiding structure that leads to five techno-economic control objectives. This work also uses five lifecycle properties to integrate rather than decompose the engineering design. The lifecycle properties core to the power grid are dispatchability, flexibility, forecastability, stability, and resilience. The use of these five properties avoids overlap in function of solutions.

Figure 1: Guiding Structure of Argument

Using such a holistic paradigm for techno-economic assessment, the journal paper conducts the most comprehensive review of renewable energy studies completed to date. It found several limitations to the existing renewable energy integration studies. Firstly, in order to address the holistic nature of the power grid, the real potential of demand side resources needs to be included. Additionally, for power grid balancing, validated simulations rather than statistical methods based on questionable assumptions need to be used. Furthermore, the consistency between future development of the real market structure and modeling methods needs to be assured. Finally, the investment costs related to the support of the future power grid need to be considered in simulation.

Thus, the paper concludes based on the defined model requirements and the assessment of the current literature, that a framework for holistic power grid enterprise control assessment needs to satisfy the following requirements:

Allows for an evolving mixture of generation and demand as dispatchable energy resources

Allows for an evolving mixture of generation and demand as variable energy resources

Allows for the simultaneous study of transmission and distribution systems

Allows for the time domain simulation of the convolution of relevant grid enterprise control functions

Allows for the time domain simulation of power grid topology reconfiguration in operation time scale

Represents potential changes in enterprise grid control functions and technologies as impacts on these dynamic properties

Accounts for the consequent changes in operating cost and the required investment costs.

These requirements have been realized in a power grid enterprise control simulator that was used for an extensive study of renewable energy integration in the power grid [Link 1], [Link 2]. The simulator includes the physical electrical grid layer and incorporates primary, secondary, and tertiary control functions. This model fits the requirements of the holistic enterprise control method as defined previously.

Demand response is an integral part of a reliable and cost-effective power grid. As wind and solar energy become two important power generation sources that reduce CO2 emissions and ensure domestic energy security, their intermittent and uncertain nature poses operational challenges on the electrical grid’s reliability. Instead of relying solely on dispatchable generation, power grid operators, called ISOs, are adopting Demand Response (DR) programs to allow customers to adjust electricity consumption in response to market signals. These DR programs are an efficient way to introduce dispatchable demand side resources that mitigate the variable effects of renewable energy, enhance power grid reliability and reduce electricity costs. Fortunately, the U.S. Supreme Court’s recent ruling Federal Energy Regulatory Commission vs. Electric Power Supply Association, has upheld the implementation of Demand Response allowing its role to mature in the coming years.

Despite the recognized importance and potential of DR, the academic and industrial literature have taken divergent approaches to its implementation. The popular approach in the scientific literature uses the concept of “Transactive Energy” which works much like a stock market of energy; where customers provide bids for a certain quantity of electricity that they wish to consume. Meanwhile industrial implementations (such as those described by FERC order 745) compensate customers according to their load reduction from a predefined electricity consumption baseline that would have occurred without DR. Such a counter-factual baseline may be erroneous. At the LIINES, we have rigorously compared the two approaches. Our previous journal paper published at Applied Energy “Demand side management in a day-ahead wholesale market: A comparison of industrial & social welfare approaches” conducted the comparison in a day-ahead wholesale market context. It showed, both analytically and numerically, that the use of power consumption baselines in demand response introduces power system imbalances and costlier dispatch.

Our recent paper now expands the analysis from a single day-ahead electricity market to the multiple layers of wholesale markets found in many regions of the North American power grid. This holistic analysis includes the day-ahead, real-time, and ancillary service markets. The integration of these multiple layers of power system operations captures the coupling between them and reveals the the impacts of DR implementation over the course of a full-day with a granularity of tens of seconds. The paper quantifies both the technical and economic impacts of industrial baseline errors in the day-ahead and real-time markets, namely their impacts on power system operating reserve requirements, operating costs and market prices.

The paper concludes that the presence of demand baseline errors – present only in the industrial implementaiton – leads to a cascade of additional system imbalances and costs as compared to the Transactive Energy model. A baseline error introduced in the day-ahead market will increase costs not just in the day-ahead market, but will also introduce a greater net load error residual in the real-time market causing additional costs and imbalances. These imbalances if left unmitigated degrade system reliability or otherwise require costly regulating reserves to achieve the same reliability.

An additional baseline error introduced in the real-time market further compounds this cascading effect with additional costs in the real-time market, amplified downstream imbalances, and further regulation capacity for its mitigation.

Based on these results, the potential for baseline inflation should be given attention by federal energy policy-makers. The effects of industrial baseline errors can be mitigated with effective policy. As a first solution, ISOs could calculate demand response baselines using the same methods of load prediction normally used in energy markets. Such an approach leaves less potential for baseline manipulation. A more comprehensive solution to this problem will be the upcoming trend of transactive energy and would eliminate the concept of baselines and their associated uncertainties entirely.

Electric power is required to produce, treat, distribute, and recycle water while water is required to generate and consume electricity. Naturally, this energy-water nexus is most evident in multi-utilities that provide electricity and water but still exists when the nexus has distinct organizations as owners and operators. Therefore, the sustainability question that arises from energy-water trade-offs and synergies is very much tied to the potential for economies of scope.

Furthermore, in the Middle East and North Africa (MENA) region, multi-utilities are not only common, but also the nexus is particularly exacerbated by the high energy intensity of the water supply due to limited fresh water resources. Several accelerating trends are increasingly stressing the existing supply systems of MENA countries: Increased demand due to population and economic growth, a more extreme and unpredictable climate mostly affecting water supply and power demand, and multiple drivers for more electricity-intensive water and more water-intensive electricity including aging infrastructure and certain regulations and standards. This paper identifies and motivates several opportunities for enhanced integrated operations management and planning in the energy-water nexus in multi-utilities in the MENA.

From the discussion of the coupling points between the energy and water systems and operations management strategies to optimize these coupling points, several policy implementations can be drawn. First, the existing approaches to dispatch of the individual products of power and water could be replaced by integrated energy-water dispatch. Second, existing fixed power and water purchase agreements can be replaced with a seamlessly integrated energy-water dispatch. As in liberalized power systems, multiple time horizon markets with their respective clearing mechanisms would be required so as to provide dynamic incentives for greater cost and resource efficiency. Fourth, the energy-water nexus also presents coupling points that engage the demand side of both power and water. Carefully designed demand-side management schemes, perhaps in the form of public-private partnerships, could present a vehicle for coordinating these coupling points in a cost-effective fashion.

The report also leads to several central policy implications. First, if water consumption and withdrawal of power generation were monetized, the investment case for renewable energy would inevitably be a stronger one. Next, while reverse osmosis desalination plants limit the energy-intensity of water production, from an integrated systems perspective, multi-stage flash plants provide a coproduction functionality that may be preferred over individual reverse osmosis and power generation facilities. Third, while many water utilities across the region have made extensive efforts towards reducing water leakages, such efforts could be strengthened by considering the embedded energy and the associated economic and environmental cost of these leakages. Lastly, there exists both a necessity and opportunity to reduce the energy footprint of water supply in MENA countries through increased water recycling. Utilizing a decentralized treatment system providing multiple water qualities and treatment levels will allow more opportunities for recycled water use in industry, agriculture, and other areas.

In all, the integrated energy-water nexus planning models and optimization programs presented and cited in this work provide deeper perspectives than their single product alternatives found in the existing literature. Their application in the policy domain has a high potential for future work and extension in the MENA region. Furthermore, these techniques have the potential for use in regions of similar climate (e.g. South-West United States & Australia) or other electricity-water utilities around the globe.

Electrified transportation has emerged in recent years as a means to reduce CO2 emissions and support energy efficiency. For this trend to succeed in the long term, electric vehicles must be integrated into the infrastructure systems that support them. Electric vehicles couple two such large systems; the transportation system and the electric power system into a nexus.

Electric vehicle integration, much like solar PV and wind integration years ago, has been fairly confined to small fleets of tens of vehicles. Such small pilot projects do not present a significant technical challenge. Their large scale adoption, however, must be carefully studied to avoid degrading overall infrastructure performance. Transportation electrification test cases serve to study infrastructure behavior well before reaching a full deployment of electric vehicles. Such a test case would resemble those often used in power systems engineering to serve methodological development in the design, planning, and operation of such systems.

The arguments for a test case to study the transportation electricity nexus are five-fold. First, a standardized test case is required to test, and compare analytical methods. In power systems, test cases served an essential role in the maturation of power flow analysis, stability studies, and contingency analysis. The transportation-electricity nexus will ultimately also require similar assessments. Secondly, using real data from critical infrastructure may be imprudent. For example, real data may reveal weak points in a power system which may be exploited by unauthorized personnel. Thirdly, a test case serves to support fundamental understanding by broadening intuition development. For the transportation-electricity nexus, understanding the effect of increasingly interdependent dynamics, will result in new requirements for optimization and control for its planning and operation. Naturally, this new found intuition serves the fourth reason of methodological development. A test case serves facilitates the design, planning, and operation of the system before it is built. Unexpected behaviors may be identified in an early stage and can subsequently be avoided or mitigated. Finally, the privacy of personal data is protected through using a test case. Transportation simulation requires microscopic data (tracking each vehicle through a full day’s events), which raises grave privacy and ethical concerns if real data is used.

To address these needs, the proposed test case includes three structural descriptions: a transportation system topology, an electric power topology, and a charging system topology. Additional data includes transportation demand and charging demand. The test case consists of a number of desirable characteristics, including completeness, functional heterogeneity, moderate size, regular topology, regular demand data, realism, and objectivity. The figure below shows the three topologies; a fully detailed description test casenamed ‘Symmetrica’ is available in the paper.

The transportation electrification test case can potentially be used for research within planning and operation management applications. A recent study (Al Junaibi et al. 2013) showed that the planning of the charging system as the couple of two infrastructure systems highly impacts the overall performance of the transportation electrification nexus. Matching the spatial layout of charging infrastructure to the demand for electrified transportation is key a infrastructure developent challenge. Furthermore, investment costs to upgrade power lines and transformers must be matched to the expected adoption of electric vehicles, providing an interesting starting point for return-on-investment and operations research methods. Using operation management applications such as charging station queue management or vehicle-2-grid stabilization could optimize the integration of electric vehicles within the nexus. Opportunities such as these present rich applications areas which have the potential to significant reduce the extra expenditure in infrastructure investments.

On Tuesday May 17, 2016, Prof. Amro M. Farid presented at the Third International Conference and Workshop on Transactive Energy Systems in Portland, Oregon. The presentation entitled: “Microgrids as a Key Enabling Transactive Energy Technology for Resilient Self-Healing Power Grid Operation” featured some of the LIINES’ recent research on resilience in power systems.

Building upon the recent IEEE Vision for Smart Grid Controls, the presentation advocated the concept of resilience self-healing operation in future power grids. This continues to be an important area of LIINES research and has been the subject of several recent blogposts. (See here, here and here). The concept of resilient power systems effectively means that healthy regions of the grid can continue to operate while disrupted and perturbed regions bring themselves back to normal operation. A key technology enabling this resilience is microgrids because they are often able to island themselves from the rest of the grid and continue to operate successfully. In this presentation, the microgrids were controlled with a transactive energy control architecture that couples several control layers to achieve both technical reliability as well as cost effectiveness. Furthermore, the presentation showed the ability for several microgrids to self-coordinate so as to demonstrate “strength-in-numbers” when adverse power grid conditions like net load ramps and variability arise. The presentation concluded with the need for significant new research where transactive energy control concepts are intertwined with recent work on power grid enterprise control.

On April 27th, 2016, Prof. Amro M. Farid gave an invited lecture at the Utility Variable-Generation Integration Group (UVIG) Spring Technical Workshop held in Sacramento, CA. The presentation entitled: “Enterprise Control as a Holistic Assessment Method for Variable Generation & Demand Response Integration” featured many of the LIINES’ research on renewable energy integration assessment methodologies.

The presentation advocated the concept of “Power Grid Enterprise Control” which has been the subject of several recent blogposts. (See here and here). Traditionally, power system operation & control methods are conducted individually. In contrast, “Power Grid Enterprise Control” integrates these methods into a single simulation of how a power system enterprise behaves as a physical power grid tied to multiple layers of control, optimization and market behavior. Such an integrated approach provides techno-economic performance results of the power grid. Furthermore, it highlights trade-off decisions between technical reliability and cost performance. The presentation showed how enterprise control simulation can be used to study renewable energy, energy storage, and demand-side energy resources.

Good science is reproducible. This means that it must be publicly available, its contributions transparently communicated, and its data accessible. These are principles that drive the everyday work of every individual’s research at the LIINES. We now wish to go further and make a commitment to Open-Information.

Beginning today, the LIINES will seek to leverage its website to make all of its research 100% reproducible by the public at large. This includes:

Sharing all input datasets used to conduct the research for which no prior proprietary or security commitments have been made.

Producing scientific publications in such a way that scientific peers can accurately verify & validate the work.

Making the content of all conference, journal and book-chapter publications freely available in author preprint form. (Note: Most publishers allow self-archiving and open-distribution of author preprints).

We believe that the LIINES’ research has broad applicability to academia, industry, government and the public at large. However, traditional publication venues are often only subscribed by academic universities and a handful of well-funded industrial companies. All-too-often the people that can benefit from this work, never get a chance to see it. This slows down the work’s potential impact and is counter to the LIINES mission. It is for these reasons, that the LIINES makes its Open-Information commitment.

While it is natural that making all of this information available will take some time, we will be sure to keep blogging to keep you up to date of new additions to the LIINES website. For now, feel free to visit the LIINES Datasets Repository which includes both data from our publications as well as a collation of several relevant and openly available datasets.

One major disciplinary expertise at the Laboratory for the Intelligent Integrated Networks for Engineering Systems is operations management and research. Naturally, using optimization techniques in the form of mathematical programming is an essential aspect of this competence. One really useful software package to allow the straightforward numerical optimization is the General Algebraic Modeling System (GAMS) and it has been used extensively in the smart power grid application domain. Many researchers in the field also link Matlab to GAMS using the former for data processing and results visualization and the latter as a solver.

The implementations at the LIINES, however, have some challenging implementation demands. For example, model predictive control problems require the solution of a numerical optimization at every discrete time step simulation evolution. When Matlab calls GAMS — on the Windows platform — it spawns a new graphical user interface integrated development environment (GUI-IDE) window (and all associated dynamic link libraries). This slows down simulation tremendously. Even worse, the Windows OS may not be able to reliably handle these repeated calls leading to a crash of the simulation. Trust us, when you are many hours into a fully automatic simulation, that’s hardly what you are looking for.

Fortunately, the GAMS version of Linux and Mac OS X does not have a GUI-IDE and runs purely from the command line. We have found this to be not just faster for simulation but also much more stable when tied to MATLAB. We highly suggest this approach.

Now some will say, that they need the GAMS GUI-IDE for development. We agree that this can be useful! Fortunately, you can have the best of both worlds. Use the command line native Linux/Mac OS X version for reliable simulation. In the meantime, a Windows version installed over WINE can be used purely for development. The GAMS support page provides very clear installation instructions here.